Exploring associations between built environment and crash risk of children in school commuting

被引:3
作者
Wu, Yaxin [1 ]
Hu, Xiaowei [1 ]
Ji, Xiaofeng [2 ]
Wu, Ke [3 ]
机构
[1] Harbin Inst Technol, Sch Transportat & Sci Engn, Harbin 150090, Peoples R China
[2] Kunming Univ Sci & Technol, Fac Transportat Engn, Kunming 650504, Peoples R China
[3] Hongyousoft Co Ltd, Karamay 834000, Peoples R China
关键词
Built environment; Crash risk in school commuting; Spatio-temporal heterogeneity; Crash scale; Mixed geographically weighted regression; Children; GEOGRAPHICALLY WEIGHTED REGRESSION; MOTOR VEHICLE COLLISIONS; LAND-USE; PEDESTRIAN INJURY; SPATIAL VARIATION; TRAFFIC SAFETY; JOINT ANALYSIS; TRAVEL MODE; URBAN FORM; WALKING;
D O I
10.1016/j.aap.2023.107287
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
Understanding how built environment are associated with crash risk (CR) in school commuting is essential to improving travel safety through land use and transportation policies. Scholars often assume that this relationship is consistent across space, but this may lead to inconsistent estimates. To address this issue, using data in Shenzhen, China, the data covers traffic accident data of children taken from police incident reports and supplemented with local land use, transportation network and specific school information. The measurement model of crash scale was conducted to represent crash severity, and the CR was further quantified. The study applies three models, spatial dubin model (SDM), geographically weighted regression (GWR), and mixed GWR (MGWR), to explore spatio-temporal heterogeneity relationships between built environment attributes and CR of children in school commuting. The findings reveal that the crash scale can better represent crash severity of school commuting than a single indicator. Policy interventions should be targeted at specific spatial scales, school types, and time windows to effectively improve travel safety. However, there are some common findings. It is recommended to use a scale of 200 m to explain the relationship between the variables. The MGWR model outperforms the other two models. To reduce CR, it is important to consider lower road network density, a reasonable layout of educational facilities, fewer bus routes, and more on-street parking spaces. Our findings can help to enrich the understanding of associations between land use and CR of children, as well as offer local planning and operating guidance for creating child-friendly environment.
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页数:20
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